Statistics Ch 13

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. The number of degrees of freedom corresponding to within treatments is

60

Exhibit 13-5 Part of an ANOVA table is shown below. Refer to Exhibit 13-5. The mean square between treatments (MSTR) is

60

In the ANOVA, treatment refers to

different levels of a factor

An experimental design that permits statistical conclusions about two or more factors is a

factorial design

Exhibit 13-5 Part of an ANOVA table is shown below. Refer to Exhibit 13-5. The mean square within treatments (MSE) is

20

Exhibit 13-5 Part of an ANOVA table is shown below. Refer to Exhibit 13-5. The test statistic is

3

An ANOVA procedure is used for data that was obtained from four sample groups each comprised of five observations. The degrees of freedom for the critical value of F are

3 and 16

The critical F value with 8 numerator and 29 denominator degrees of freedom at α = 0.01 is

3.20

In an analysis of variance problem if SST = 120 and SSTR = 80, then SSE is

40

In a completely randomized design involving three treatments, the following information is provided: The overall mean for all the treatments is

7.25

The F ratio in a completely randomized ANOVA is the ratio of

MSTR/MSE

Which of the following is not a required assumption for the analysis of variance?

Populations have equal means.

When an analysis of variance is performed on samples drawn from K populations, the mean square between treatments (MSTR) is

SSTR/(K - 1)

The variable of interest in an ANOVA procedure is called

a factor

The number of times each experimental condition is observed in a factorial design is known as

replication

In the analysis of variance procedure (ANOVA), "factor" refers to

the independent variable

Exhibit 13-1 SSTR = 6,750 H0: m1=m2=m3=m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 13-1. The mean square within treatments (MSE) equals

500

Exhibit 13-5 Part of an ANOVA table is shown below. Refer to Exhibit 13-5. If at 95% confidence, we want to determine whether or not the means of the populations are equal, the p-value is

between 0.05 to 0.1

An experimental design where the experimental units are randomly assigned to the treatments is known as

completely randomized design

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. The mean square within treatments (MSE) is

10

In an analysis of variance problem involving 3 treatments and 10 observations per treatment, SSE = 399.6. The MSE for this situation is

14.8

Exhibit 13-1 SSTR = 6,750 H0: m1=m2=m3=m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 13-1. The mean square between treatments (MSTR) equals

2,250

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. The number of degrees of freedom corresponding to between treatments is

4

Exhibit 13-1 SSTR = 6,750 H0: m1=m2=m3=m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 13-1. The test statistic to test the null hypothesis equals

4.5

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. The test statistic is

5.0

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. The mean square between treatments (MSTR) is

50.00

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square Refer to Exhibit 13-4. The sum of squares within treatments (SSE) is

600

Exhibit 13-1 SSTR = 6,750 H0: m1=m2=m3=m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 13-1. The null hypothesis is to be tested at the 5% level of significance. The p-value is

between .01 and .025

Exhibit 13-1 SSTR = 6,750 H0: m1=m2=m3=m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 13-1. The null hypothesis

should be rejected

The ANOVA procedure is a statistical approach for determining whether or not

the means of two or more populations are equal

Exhibit 13-4 In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 13-4. If at 95% confidence we want to determine whether or not the means of the five populations are equal, the p-value is

less than 0.01 Save